Combine data from multiple accounts and/or multiple views into one data set. Deliver it to Google Data Studio or Klipfolio to build awesome dashboards.
Case: 88 GA views in a Klipfolio dashboard
For one of our partners we collect data from 88 Google Analytics views from several properties, add logic (to be used in the dropdowns in the Klipfolio dashboard) combine it in one data set and deliver it to Klipfolio as a datasource, refreshed every hour during daytime.
This saves a lot of complexity in the Klipfolio formula's, avoids dynamic datasources and keeps the Klipfolio dashboard really fast.
Combine data from multiple channels (like Adwords, Facebook Ads, Adform) into one data set to report on total marketing spend, conversions and ROI.
Case: Performance tab Klipfolio dashboard
For many online agencies, we deliver the data from Facebook Ads, Adwords, Twitter Ads, Adform, Bing Ads and LinkedIn Ads in a few interconnected data sets so they can easily build a cross-channel performance dashboard. See how to build multichannel dashboards here.
We make it really easy to add or remove accounts without having to change the formula's. This saves time and complexity.
Combine data from multiple channels. From each of those channels pick only those specific campaigns you need for your report.
Case: Cross-channel campaign dashboard
One of our partners creates cross-channel campaign groups for a large Pharmaceutical company to report on a specific product launch. See how to create multichannel campaign groups here.
All your channels, only specific campaigns, in one dashboard.
Targets and Benchmarks
Give context to your data by adding a target or calculated benchmarks/averages.
Case: Multiple trendlines in one Google Data Studio graph
We add targets (for spent, impressions and conversions per campaign, per month) to the Adwords data before we made it available in a Google Drive sheet. Our partners build custom Google Data Studio dashboards with this data, showing the spend vs. target in one graph. Of course, the data is refreshed every hour during office hours.
Google Data Studio graph as it should be: targets vs. actuals.
Case: Industry benchmark
For one of our partners, we calculate the industry benchmark for average transaction value in his industry based on available data and present this in the personal environment of each of his clients.
Adding context to your clients data